Category: Uncategorized

Rakesh Dhawan, BTech, MSEE, MBA

Think stack motors are rarely encountered. However, they do exist. BionX, an erstwhile Canadian Company, launched one of the known thin-stack motors in the field of electric bicycles. The large diameter motor with a 12mm stack height had some unusual characteristics. I will discuss that design in a separate post.

Some of the concerns below are about thin stack motors.

1. Increased Magnetizing Current
   • A larger air gap increases the reluctance of the magnetic circuit.
   • This requires a higher magnetizing current to maintain the same flux density, leading to higher copper losses and reduced efficiency.
2. Reduced Flux Density & Torque Production
   • The air gap is where the magnetic field transfers between the rotor and stator. A larger gap weakens this field, reducing torque production per ampere.
   • This forces designers to compensate by increasing current, which raises I²R losses and decreases efficiency.
3. Increased Leakage Flux
   • More flux escapes into unintended paths, leading to poor power factor and additional losses.
   • This can also result in weaker electromagnetic coupling between the stator and the rotor.
4. Eddy Current Losses in Thin Laminations
   • Thin stack designs rely on laminations to minimize eddy current losses, but a large air gap increases the fringing effect (flux spreading), which can induce additional losses in the edges of the laminations.
   • This can cause localized heating and performance degradation over time.
5. Structural & Mechanical Stability
   • A large air gap can make the motor mechanically unstable, leading to vibrations and noise.
   • It also demands tighter machining tolerances to maintain uniformity, increasing manufacturing complexity.
6. Torque Harmonics
   • Because of the non-linearities due to saturations in the laminations, the backEMF is no longer sinusoidal, introducing severe harmonics during torque production.

Balancing Stack Height vs. Air Gap

To optimize motor performance while maintaining thin stacks, designers must strike a balance between stack height and air gap:

1. Increase Stack Height to Compensate for Air Gap Losses
   • A taller stator stack provides more magnetic material, reducing the reluctance of the core and improving flux linkage.
   • This helps recover lost torque due to an increased air gap.
2. Optimize Air Gap Size
   • A smaller air gap is preferable for efficiency, but practical manufacturing constraints (mechanical tolerances, rotor movement, cooling needs) must be considered.
   • Using advanced high-permeability materials (e.g., silicon steel laminations) can help minimize the impact of air gap reluctance.
3. Use High Energy Permanent Magnets (for PM Motors)
   • In permanent magnet (PM) motors, stronger magnets (e.g., NdFeB) help counteract the effect of a larger air gap by maintaining sufficient flux levels.
4. Improve Slot and Tooth Geometry
   • Adjusting stator slot dimensions and tooth shape can help concentrate the flux density, making the motor more efficient even with a moderate air gap.
5. Consider Air Gap Shape Optimization (or Flux Focus techniques)
   • A graded or tapered air gap or flux focus technique (instead of uniform spacing) can help direct flux more efficiently, reducing unwanted leakage.

Conclusion

A large air gap in a motor with thin stacks leads to higher losses, lower torque, and efficiency issues. The optimal design requires balancing stack height and air gap size by:

• Increasing stack height to compensate for reluctance,
• Using high-energy magnetic materials,
• Optimizing slot, tooth, and air gap geometries,
• Keeping air gap tolerances tight while allowing for mechanical stability.

By carefully designing these factors, motor efficiency can be maximized without excessive material or energy loss.

The principles behind the operation of electric motors are a tremendous gift of nature. Uncovering those principles and focusing on their precise and accurate applications makes for an elegant and beautifully designed electric motor. I love the electric motor design, and today, I wanted to share this beautiful plot of the flux density distribution of a new IPM motor.

IPM Motor with Flux Density Contours

There’s something almost magical about how flux density distributes inside an electric motor, especially when they’re as elegantly engineered as Interior Permanent Magnet (IPM) motors.

If you’ve ever wondered why your electric car zips around so quietly or how industrial machines deliver such reliable power, IPM motors often play a key role. Here’s a quick rundown of why these motors are unique and what you’re seeing in that eye-catching color plot of flux density contours.

What Is an IPM Motor?

“IPM” stands for “Interior Permanent Magnet.” Unlike other motor types where the magnets might be placed on the outer surface of the rotor, IPM motors embed the permanent magnets inside the rotor. This gives them a few advantages:

• Enhanced Efficiency: By placing magnets within the rotor, the motor can harness magnetic and something called reluctance torque, helping it deliver higher efficiency under various speeds and loads.
• Robust Construction: Tucking magnets inside offers better mechanical protection (applicable at high rotation speeds or in demanding environments).
• Improved Performance at High Speeds: IPM motors often excel at delivering torque effectively at higher RPMs—one of the reasons they’re a big deal in electric vehicle applications.

Understanding the Flux Density Contours

The colorful image is a snapshot of the “flux density” distribution. Flux density (measured in Teslas) tells us how concentrated the magnetic field is at each point in the motor. Here’s the gist of the color-coded zones:

• Blue Regions: Typically show lower flux density. These areas might be where the field passes through less magnetic material or experiences more air gaps.
• Green to Yellow Zones: Indicate higher flux density, meaning the magnetic field is stronger there. These zones often show how the magnetic field routes through the rotor and stator teeth.
• Bright or High-Intensity Colors: If you see reds or bright yellows, those areas have powerful magnetic fields—often around the magnets or stator teeth tips.

Why It Matters

It is crucial for engineers to see how the magnetic field flows because it helps optimize the motor’s design. By tweaking magnet placement, rotor geometry, or even the materials used, designers can:

1. Maximize Torque Output: Ensuring the magnetic circuit is efficient.
2. Minimize Losses: Reduce heat and ensure you get more power for every watt of electricity going into the motor.
3. Improve Reliability: Avoiding “hot spots” or regions of mechanical stress that could lead to premature failure.

A Future of Quiet, Efficient Power

IPM motors aren’t just for cars; they pop up in everything from drones to washing machines. Their blend of efficiency, power density, and durability makes them a popular choice in modern motor-driven systems. As battery and power electronics technologies advance, IPM motors will likely become even more integral to everyday life—giving us smoother, quieter, and more energy-efficient ways to move and make things.

The 80/20 principle, also known as the Pareto Principle, suggests that roughly 80% of the effects come from 20% of the causes. When it comes to hardware design, applying the 80/20 principle can help optimize efficiency and focus resources on the most critical aspects. Here are some ways to utilize the 80/20 principle in hardware design:

1. Identify Critical Features: Determine the key functionalities and features for the hardware design’s success. Focus on the 20% of features that will deliver 80% of the value to the end-users. This allows you to allocate resources effectively and prioritize the essential elements.
2. Design for Common Use Cases: Analyze the most common use cases and requirements for the hardware. By identifying the 20% of scenarios that cover 80% of user needs, you can streamline the design process and optimize performance for those primary use cases. This approach helps avoid overengineering and unnecessary complexity.
3. Prioritize Design Constraints: Identify the critical design constraints and factors that significantly impact the hardware’s overall performance, cost, and reliability. Allocate resources and effort to optimizing these key areas, ensuring they meet the required specifications while considering the trade-offs for less critical aspects.
4. Focus on Robustness and Reliability: Identify the 20% of components, subsystems, or functionalities that are most likely to fail or cause issues. By focusing on improving their robustness, reliability, and quality, you can enhance the overall performance and longevity of the hardware. This targeted approach allows for effective resource allocation and risk mitigation.
5. Iterative Design and Feedback: Adopt an iterative design process and collect feedback from users, stakeholders, and experts. This enables you to identify the most critical areas for improvement and refine the hardware design iteratively. You can improve substantially by addressing the 20% of user satisfaction issues.
6. Continuous Improvement: Continuously assess and evaluate the hardware design to identify areas of inefficiency, waste, or redundancy. By applying the 80/20 principle to ongoing improvement efforts, you can focus on the most impactful changes resulting in the most significant overall benefit.

Remember that the 80/20 principle is a guideline and may not always be exact. The specific percentages may vary depending on the project and context. The goal is to identify the vital few factors or aspects that significantly influence the hardware design’s success and allocate resources accordingly.

At PEG, we practice an integrative approach involving Simulation in the complete product development cycle. It is important to understand the role of simulation in every phase of the product development cycle. Below is a summary of how simulation can be used in each stage:

1.  Concept Phase: 

During this phase, use simulation tools to verify circuit operation. One must start small using ideal component models and build the system in stages. Each stage work should be saved. It is important to understand the theory and state of the art behind the circuit you are about to simulate. Without proper theoretical foundation, you will not be able to obtain useful information from simulation.

Also, for majority of the engineers, a process methodology or steps to design must include simulation. Simulation is most effective when the circuit behavior is not well understood and we can construct several what-if scenarios or use simulation to build a repertoire of questions to be answered about the design problem at hand. Simulation effectiveness improves with experience and time. An engineering department must be dedicated to it. As with any other skill, to yield simulation as a potent competitive weapon, one must spend significant time and resources to hone it. A frivolous relationship or experimental tinkering with simulation tools will not yield any fruitful results.

2. Design Phase: 

During design phase, as you begin to transform your work into schematics, one must pay careful attention to component selection and component models can be incorporated (especially in Spice based tools) one at a time.

Do not be too ambitious to incorporate a host of models at one time. Also realize that incorporating each component model is never required. One must be quite prudent in incorporating essential component models. Just remember Pareto’s principle – 20% or less determine 80% or more of the outcome. This must always be kept in mind

3. Prototype Phase: 

During this phase as prototypes are built, one must pay careful attention to collecting data during incoming inspection (mechanical variables) and testing (electrical variables). Here, we always recommend to use the  suppliers who would also build production units. It is important to do so to understand supplier capabilities and process variations.

4. First Article Phase: 

During this phase as First Articles are built, one must pay careful attention to collecting data during incoming inspection (mechanical variables) and testing (electrical variables). During this phase, we use statistics to understand variable distributions and correlation between various parameters. These correlations may change from the prototype stage.

It is important to start forming new hypothesis can tremendously expedite the whole product development cycle. During this phase, at PEG, we strongly recommend using statistics to understand variable distributions and correlation between various variables.  It is important to start forming hypothesis on what could be troublesome variables which are going to effect the performance. Those variations must be incorporated into Simulations to re-characterize  the system and understand overall performance variations.

5. Pre-Production/Production Phase: 

During this phase as Pre- Production or Production units are built, one again must pay careful attention to collecting data during incoming inspection (mechanical variables), in-process inspection (mechanical and electrical variables) and final testing (electrical variables). During this phase, we use statistics to understand variable distributions and correlation between various parameters.

These correlations may change from the earlier phases. It is important to start forming fresh hypothesis on what could be troublesome variables which are going to effect the system performance. Those variations must be incorporated into Simulations to re- characterize the system and understand overall performance variations. This is the process of continuous improvement and PEG’s integrated approach, if followed rigorously, yields not only superior products but also strong infrastructure capabilities.

There is always an “Edison approach” to design. With this approach, you will need to spend countless hours and follow rigorous and scientific method of design of experiments as well as truthful collection of data. “Edison approach” is simply too expensive and unaffordable in today’s world. Nevertheless, with enough money and time, such approach is always possible.

LTSpice and PSpice are great tools for Power Electronic circuits barring their annoying and most irritating convergence problems. These convergence problems are a great waste of time and a source of frustration. However, there has been a steady rise in the tools and techniques in the Spice arena, especially for the Power Electronics and Motor Control areas. Spice and other available tools expertise can be wielded effectively in launching new products through short product development cycles. By no means, we are claiming that Spice expertise in Power Electronics alone is sufficient to cut the time from concept to production.  However, it is an important tool to have in the bag.

For Power Electronics Circuits, PEG recommends the following approach to using Spice during  the Concept Phase only:

• Before you build your own circuit model, search to see if similar circuits are available in the public domain. A great engineer always builds her/his work on what is already available. Do not reinvent the wheel.
• Always start with the most ideal circuit model of components. Simplicity is the key. Sub-circuits are great in ensuring that small parts of circuits can be made to work first. It is always prudent to use simple, well-tested models.
• Now, transient analysis using ideal components will get you only so far. Small Signal modeling is an important step in being able to overcome convergence problems as well as understand the circuit behavior fully. This technique requires state space averaging and is most vital in simulating Power Electronic circuits. PEG specializes in small signal modeling of the Power Electronic circuits and if you run into hot waters using this technique, we are happy to help.
• Control loop compensation is not a  simple matter for most of the Power Electronic circuits. However, the compensator can be easily designed using the small signal modeling techniques.
• Once the above steps are followed and we have a working simulation, we can begin to run various what-if scenarios to understand the circuit behavior in time domain as well as frequency domain.